Devices, systems, and methods for geological surface and property prediction

Abstract

A geological projection system may receive seismic survey data, the seismic survey data including a seismic surface of a geological feature. A geological projection system may receive resistivity sensor data from a downhole resistivity sensor, the resistivity sensor data being for a reference length uphole of a reference depth. A geological projection system may generate a sensed surface over the reference length using the resistivity sensor data. A geological projection system may generate a displacement field of a difference between the sensed surface and the seismic surface for the reference length. A geological projection system may apply an uncertainty model to at least one of the resistivity sensor data, the seismic survey data, or the displacement field, the uncertainty model generating an output including an uncertainty distribution of a projected surface of the geological feature downhole of the reference depth.

What is claimed is: 
     
         1 . A method, comprising:
 receiving seismic survey data, the seismic survey data including at least one seismic surface of a geological feature;   receiving resistivity sensor data from a downhole resistivity sensor, the resistivity sensor data being for a reference length uphole of a reference depth;   generating a sensed surface over the reference length using the resistivity sensor data;   generating a displacement field of a difference between the sensed surface and the seismic surface for the reference length; and   applying an uncertainty model to at least one of the resistivity sensor data, the seismic survey data, or the displacement field, the uncertainty model generating an output including an uncertainty distribution of a projected surface of the geological feature downhole of the reference depth.   
     
     
         2 . The method of  claim 1 , further comprising adjusting at least one drilling parameter based on the projected surface and the uncertainty distribution. 
     
     
         3 . The method of  claim 1 , wherein the resistivity sensor data is first resistivity data, the reference depth is a first reference depth, the sensed surface is a first sensed surface, the uncertainty distribution is a first uncertainty distribution, and the projected surface is a first projected surface, and further comprising:
 receiving second resistivity data from the downhole resistivity sensor for the reference length uphole of a second reference depth;   determining a second sensed surface over the reference length uphole of the second reference depth using, at least in part, the second resistivity data;   determining a second displacement field between the second sensed surface and the seismic surface for the reference length uphole of the second reference depth; and   applying the uncertainty model to at least one of the second resistivity data, the seismic survey data, or the second displacement field, wherein the uncertainty model generates an output including a second uncertainty distribution of a second projected surface up the geological feature downhole of the second reference depth.   
     
     
         4 . The method of  claim 1 , wherein the output of the uncertainty model further includes, based on the uncertainty distribution, an expected projected surface, an upper projected surface, and a lower projected surface. 
     
     
         5 . The method of  claim 1 , wherein applying the uncertainty model includes applying a correlation function correlating the sensed surface to the seismic surface over the reference length uphole of the reference depth. 
     
     
         6 . The method of  claim 1 , wherein applying the uncertainty model includes applying a correlation function correlating the displacement field to the projected surface over the reference length uphole of the reference depth. 
     
     
         7 . The method of  claim 1 , further comprising determining a covariance of the resistivity sensor data and wherein the uncertainty distribution outputted from the uncertainty model is based at least in part on the covariance for the reference length. 
     
     
         8 . The method of  claim 7 , wherein determining the covariance is based on measurement uncertainty of the resistivity sensor data. 
     
     
         9 . The method of  claim 1 , further comprising determining a covariance of the seismic survey data and wherein the uncertainty distribution outputted from the uncertainty model is based at least in part on the covariance for the reference length. 
     
     
         10 . The method of  claim 9 , wherein determining the covariance is based on a measurement uncertainty of the seismic survey data. 
     
     
         11 . The method of  claim 9 , wherein determining the covariance is based on a measurement uncertainty of an interpolation between reference offset wellbores. 
     
     
         12 . The method of  claim 1 , wherein determining the displacement field includes determining a bulk shift and a displacement of the seismic surface to the sensed surface. 
     
     
         13 . The method of  claim 1 , wherein the uncertainty distribution includes a three-dimensional surface ahead of the reference depth. 
     
     
         14 . A computing system, comprising:
 a processor and memory, the memory including instructions which, when accessed by the processor, cause the processor to:
 receive seismic survey data, the seismic survey data including a seismic surface of a geological feature; 
 receive resistivity sensor data from a downhole resistivity sensor, the resistivity sensor data being for a reference length uphole of a reference depth; 
 generate a sensed surface over the reference depth using the resistivity sensor data; 
 generate a displacement field of a difference between the sensed surface and the seismic surface for the reference length; and 
 apply an uncertainty model to at least one of the resistivity sensor data, the seismic survey data, or the displacement field, the uncertainty model generating an output including an uncertainty distribution of a projected surface of the geological feature downhole of the reference depth. 
   
     
     
         15 . The computing system of  claim 14 , wherein the instructions further cause the processor to adjust at least one drilling parameter based on surface uncertainty of the projected surface. 
     
     
         16 . The computing system of  claim 14 , wherein applying the uncertainty model includes applying a correlation function correlating the sensed surface to the seismic surface over the reference length uphole of the reference depth. 
     
     
         17 . The computing system of  claim 14 , further comprising determining a covariance of the resistivity sensor data and wherein the uncertainty distribution outputted from the uncertainty model is based at least in part on the covariance for the reference length. 
     
     
         18 . The computing system of  claim 17 , wherein determining the covariance is based on measurement uncertainty of the resistivity sensor data. 
     
     
         19 . The computing system of  claim 14 , further comprising determining a covariance of the seismic survey data and wherein the uncertainty distribution outputted from the uncertainty model is based at least in part on the covariance for the reference depth. 
     
     
         20 . A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to perform a method for interpreting drilling dynamics data, the method comprising:
 receiving seismic survey data, the seismic survey data including at least one seismic surface of a geological feature;   receiving resistivity sensor data from a downhole resistivity sensor, the resistivity sensor data being for a reference length uphole of a reference depth;   generating a sensed surface over the reference length using the resistivity sensor data;   generating a displacement field of a difference between the sensed surface and the seismic surface for the reference length; and   applying an uncertainty model to at least one of the resistivity sensor data, the seismic survey data, or the displacement field, the uncertainty model generating an output including an uncertainty distribution of a projected surface of the geological feature downhole of the reference depth.